Authors:
David James McCorrie
;
Elena Gaura
;
Keith Burnham
and
Nigel Poole
Affiliation:
Coventry University, United Kingdom
Keyword(s):
Signal Reconstruction, Optimization Problems in Signal Processing, Change Detection Problems Instrumentation Networks and Software.
Related
Ontology
Subjects/Areas/Topics:
Business Analytics
;
Change Detection
;
Data Engineering
;
Engineering Applications
;
Informatics in Control, Automation and Robotics
;
Instrumentation Networks and Software
;
Intelligent Control Systems and Optimization
;
Optimization Problems in Signal Processing
;
Robotics and Automation
;
Signal Processing, Sensors, Systems Modeling and Control
;
Signal Reconstruction
Abstract:
In a wireless sensor network, transmissions consume a large portion of a node’s energy budget. Data reduction
is generally acknowledged as an effective means to reduce the number of network transmissions, thereby
increasing the overall network lifetime. This paper builds on the Spanish Inquisition Protocol, to further reduce
transmissions in a single-hop wireless sensor system aimed at a gas turbine engine exhaust gas temperature
(EGT) monitoring application. A new method for selective filtering of sensed data based on state identification
has been devised for accurate state predictions. Low transmission rates are achieved even when significant
temperature step changes occur. A simulator was implemented to generate flight temperature profiles similar to
those encountered in real-life, which enabled tuning and evaluation of the algorithm. The results, summarized
over 280 simulated flights of variable duration (from approximately 58 minutes to 14 hours) show an average
reduction in the
number of transmissions by 95%, 99.8% and 91% in the take-off, cruise and landing phases
respectively, compared to transmissions encountered by a sense-and-send system sampling at the same rate.
The algorithm generates an average error of 0:11 +/- 0:04 °C over a 927 °C range.
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